Llm Application Dev

Name: Llm Application Dev
Author: julianromli

Checked

julianromli·vlatest·ai-ml

Provides LLMs guidance and assistance for building AI and machine learning applications.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

Run this in your project

terminal

$ npx skills add julianromli/opencode-template --skill llm-application-dev -a claude-code

Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

julianromli

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned 2 Oct 2026

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned julianromli/opencode-template at 37ceab2d64.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit: 37ceab2d64
Manifest: skill/llm-application-dev/SKILL.md
Scanned: 1 file, 197 lines

This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.

What each check looks for →

About this skill

What it does

This skill allows AI agents to develop applications using Large Language Models (LLMs). It facilitates the creation of functional code, including generating and executing Python scripts, and can be used for tasks like data analysis or automating workflows. The agent can also debug existing code and provide explanations for its functionality.

When to use it

Automating repetitive coding tasks: Generate boilerplate code or implement common algorithms quickly.
Debugging existing applications: Identify and fix errors in Python scripts.
Learning new programming concepts: Get explanations of code snippets and how they work.
Rapid prototyping: Quickly build and test application ideas using LLMs.

Key capabilities

Code generation (Python)
Code execution
Debugging assistance
Code explanation

Example prompts

"Write a Python script to calculate the average of a list of numbers."
"Debug this Python code: [insert code here]"
"Explain what this function does: [insert code here]"

Tips & gotchas

The skill requires access to a Python interpreter for code execution. Complex applications may require iterative refinement and debugging with the agent.